Various types of methods and approaches are available to predict the intelligibility of speech
signals, but many of these still suffer from two major problems: first, their required prior …

Future wireless communication systems are facing with many challenges due to their
complexity and diversification. Orthogonal frequency division multiplexing (OFDM) in 4G …

Emotion information from speech can effectively help robots understand speaker's intentions
in natural human-robot interaction. The human auditory system can easily track temporal …

Continuous dimensional emotion recognition from speech helps robots or virtual agents
capture the temporal dynamics of a speaker's emotional state in natural human–robot …

This paper presents a revised version of the Hearing-Aid Speech Perception Index (HASPI).
The index is based on a model of the auditory periphery that incorporates changes due to …

An accurate objective prediction of human speech intelligibility is of interest for many
applications such as the evaluation of signal processing algorithms. To predict the speech …

The reverberation time (RT) and the early-to-late reverberation ratio (ELR) are two key
parameters commonly used to characterize acoustic room environments. In contrast to …

Many individuals struggle to understand speech in listening scenarios that include
reverberation and background noise. An individual's ability to understand speech arises …

Automatic speech recognition (ASR) has made major progress based on deep machine
learning, which motivated the use of deep neural networks (DNNs) as perception models …

This paper presents a speech intelligibility model based on automatic speech recognition
(ASR), combining phoneme probabilities from deep neural networks (DNN) and a …